PREDIKSI CURAH HUJAN KOTA SEMARANG DENGAN FEEDFORWARD NEURAL NETWORK MENGGUNAKAN ALGORITMA QUASI NEWTON BFGS DAN LEVENBERG-MARQUARDT

*Budi Warsito -  Mathematics Department Diponegoro University, Indonesia
Sri Sumiyati -  Environmental Engineering Department Diponegoro University, Indonesia
Published: 1 Sep 2007.
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Section: Review Article
Language: EN
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Abstract
This paper study the rainfall prediction at Semarang City as time series data with Feed Forward Neural Network  (FFNN)  model.  The  learning  algorithm  that  be  used  are  the  Quasi  Newton BFGS and Levenberg-Marquardt algorithm. The input unit is determined based on the best of ARIMA model. The computation is done with use  Matlab 7.1 program with 1000 epoch, five unit of hidden layer, 100 replication  and use  input at lag  variabel  1,  12  and 13, respectively. The result shows that the prediction is good in relatively, where Quasi Newton BFGS algorithm result the Mean Square Error (MSE) that more accurate.
Keywords
FFNN, Quasi Newton BFGS, Levenberg-Marquardt, rainfall

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